The Winchester Mystery House in AI: DSPy, Flex optimizer, and the cost of feedback loops
dbreunig · x · 2026-08-25
A deep dive into AI engineering featuring Drew Breunig. The discussion covers the 'Winchester Mystery House' problem: what happens when code is so cheap that feedback is the only bottleneck left. It explores the DSPy framework in detail, including Signatures, the GEPA optimizer, and the new Flex optimizer, which rewrites code instead of just prompts, with real-world before-and-after results on cost and accuracy. The conversation also touches on why AI-built apps look identical, the difference between agents and workflows, and the shift of models from infrastructure to appliances.
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